This invention relates to automated railway component inspection, and more particularly to a method and system for anomalous railway component detection.
To maintain safe and efficient operations, railroads typically inspect their tracks for physical defects on a regular basis. Such track inspection normally covers a wide spectrum. Some of these measurements have been automated using a track geometry car, yet others are still manually conducted.
For example, one inspection that is currently manually performed is the monitoring of spiking patterns. A spiking pattern is the layout of spikes on a tie plate, which hold the plate in place to prevent the rail from latitudinal movement. A spiking pattern is defined over two tie plates which fasten one tie. There are 8 spike slots on each tie plate. Consequently, a spiking pattern is determined by the status of 16 spike slots, which could either be spiked or empty.
Based on the class of track, the tonnage and speed of trains traveling on it, and its degree of curvature, a specific spiking pattern will be required for a specific track segment. Applying wrong or noncompliant spiking patterns could potentially lead to derailment. On the other hand, when previously installed spikes are broken or fall off the plate, it will also change the spiking pattern. Furthermore, tie plates of any non-compliant spiking patterns are considered as anomalous tie plates.
Currently, anomaly detection methods have been applied to detection of unusual video events, abnormal object motion patterns, and abnormal vehicle movements. These methods have used trajectory based processes where an appearance model is built to track objects, activity learning techniques where various statistical models are used to learn object activities, or clustering-based techniques where normal or acceptable patterns are pre-grouped into clusters, and anomalies are identified by detecting outliers.
However, railway components are static objects, so most existing solutions will not be applicable. Moreover, clustering analysis is impractical due to the high number of component patterns; for example, in the analysis of tie plates there are 216 possible patterns per tie. As such, many railroad inspections are still manually and visually conducted by railroad track inspectors.